巴西与危地马拉：35 °C 以上天数

2014 年35 °C 以上天数：巴西为 18.8 天，危地马拉为 16.9 天（CMIP6 气候模型中位数模拟）。 2014 年巴西的数值较高，高出 1.9 天，是危地马拉的 1.11 倍。

每年天数 · CMIP6

巴西危地马拉CMIP6 模型中位数（SSP2-4.5，中间路径）模型第 10–90 百分位

数据解读

自 2011 年超过危地马拉以来，巴西的数值一直更高。
根据CMIP6 模型中位数（SSP2-4.5，中间路径），2100 年巴西为 80.8 天，危地马拉为 47.9 天。

逐年数据

每年天数 · CMIP6

年份	巴西	危地马拉
2014	18.8	16.9
2013	21.8	15.5
2012	19.5	15.4
2011	19.6	14.9
2010	15.4	17.5
2009	16.6	13.6
2008	14.6	14.5
2007	11.6	15.2
2006	12	14.5
2005	14.2	14.1
2004	16.2	13.7
2003	15.5	13.4
2002	12.4	13.5
2001	16.1	14.5
2000	13.5	12.9
1999	11.4	12.6
1998	12.8	11
1997	11.7	11.9
1996	10	10.7
1995	8.8	9
1994	9.1	10.3
1993	7.8	11
1992	5.6	8.9
1991	8.5	12.5
1990	13.3	13.4
1989	10.2	10.6
1988	9.7	10.1
1987	9.4	10
1986	9.9	12.2
1985	7.5	8.2
1984	7	7.4
1983	6.4	9
1982	8.5	11.1
1981	9.4	12
1980	8.1	8.5
1979	9.1	10.9
1978	9	8.5
1977	8	11
1976	6.9	10.3
1975	6.8	9
1974	7.1	10.5
1973	7.3	8.8
1972	7	10.2
1971	5.8	7.9
1970	6.7	9.2
1969	6.9	10.1
1968	6.4	8.6
1967	6.4	8.1
1966	6.4	8.2
1965	6	7.4
1964	5.9	9.2
1963	4.9	9.6
1962	7.2	10.1
1961	7.5	10.6
1960	7.8	10
1959	7.5	9.5
1958	7.9	9.3
1957	8	9.3
1956	6.9	8.7
1955	8.6	9.9
1954	8.3	8.9
1953	6.8	9.2
1952	7.2	9.6
1951	7.2	8.6
1950	7.7	8.5

CMIP6 模型中位数（SSP2-4.5，中间路径） · 2015–2100

年份	巴西	危地马拉
2015	18.56.9–38.8	19.39.9–31.9
2016	18.57–35.9	16.19.8–23.4
2017	19.47.7–41.4	17.98.3–27.3
2018	19.87.6–41.4	17.610–28.9
2019	218.9–47.1	16.88.8–30.9
2020	21.98.7–43.2	19.29.2–30
2021	24.69.7–51.8	18.311–28.2
2022	23.410–51.2	20.211.8–31.7
2023	25.710.5–55.5	18.210.7–35.1
2024	27.713.3–51.1	23.112.3–35.2
2025	27.210.5–57.6	21.610.6–36
2026	24.48.1–53.1	19.59.8–35.1
2027	28.28.9–55.7	19.310.5–34.7
2028	29.411.9–61.9	21.711.2–40.8
2029	33.916.4–66.7	22.911.9–38
2030	28.211.6–56.6	199–33.2
2031	35.315.2–70.7	20.111.1–36.5
2032	35.616.6–67.3	23.113–35.3
2033	3113.5–63.2	20.512.3–33.2
2034	31.214.1–75.1	21.610.3–38.1
2035	30.814.4–68	22.211.8–31.9
2036	32.413.7–58.7	23.513.6–33.7
2037	39.419.6–66.5	25.114.3–37.8
2038	38.215.4–71.3	26.613.9–40.6
2039	37.214.6–75.5	26.514.9–41.2
2040	38.518.6–76.2	24.811.2–37.4
2041	41.819.9–76.6	22.411.3–40.7
2042	39.917–86.1	26.412–41.9
2043	37.614.9–81.2	26.815.7–50.1
2044	38.416.1–84.4	25.912.8–48
2045	40.420.4–74.9	26.412.9–47.2
2046	5023.7–86.7	30.916.1–47.6
2047	43.522.9–86.4	29.918.1–49
2048	50.424.6–96.2	28.816.9–44
2049	49.823.9–90.2	32.716.4–52.8
2050	46.922–92.7	27.819.1–43.8
2051	47.324.9–95.6	27.717.7–50.8
2052	54.728.7–97.5	32.917.9–52.1
2053	47.122.6–92.3	30.117.5–55.3
2054	45.221.6–92.2	30.818.1–49.5
2055	52.228.6–103.8	3219.4–52.4
2056	53.223.6–110.8	30.316.2–54
2057	50.620.2–94.7	32.416.5–52.3
2058	55.325–117.3	28.318.9–55.3
2059	61.229–118.5	36.220.3–55.5
2060	6531.1–111.3	36.619.7–57.2
2061	54.123.5–115.4	36.321.9–58.2
2062	54.924.7–127.7	33.217.3–62.6
2063	59.428.6–112.9	36.219.3–60.3
2064	54.828.7–106.1	36.120.6–55.1
2065	62.330.3–119.5	40.717.2–60.3
2066	62.330.6–113.5	37.722.4–58.7
2067	60.926.9–113.1	33.120.8–57.4
2068	66.730.1–119.7	39.626.6–57.4
2069	60.631.5–113.8	42.221–65.7
2070	59.932.1–124.8	39.319.3–58.4
2071	64.433.8–111	40.523.2–62.5
2072	6830.5–128.1	4422.5–70.5
2073	72.736–127.6	44.826.3–67.1
2074	68.832.6–125.7	37.919–60.3
2075	67.832.7–116.4	41.122.5–67.1
2076	67.933.7–124.9	40.123.5–60.6
2077	72.535.5–128.9	38.719.4–65.5
2078	7336.7–132	41.823.6–64.2
2079	69.233.6–125.5	46.120.5–67.8
2080	67.834.9–122.2	42.924.9–62.6
2081	70.936.9–140.4	42.825–65.8
2082	70.640.7–125.8	41.620.2–63.7
2083	75.735.7–152.5	39.921.5–70.8
2084	7734.1–140.3	44.125.4–73.9
2085	83.937.2–147.8	4623.7–72.1
2086	73.334.6–141	38.521–70.1
2087	78.439.2–144.2	44.324.3–73.9
2088	79.335.1–152	43.522.5–72.2
2089	75.239–146.4	37.323.7–68.2
2090	78.341.8–148.6	41.624.1–66
2091	8135.2–147.9	46.824.7–77.3
2092	7936.6–148	49.628.3–70.8
2093	7739.3–148.7	43.626.5–76.4
2094	7939.6–144.5	4527.1–75.6
2095	88.636.5–155.9	46.223.2–75.6
2096	75.736.1–152.8	43.224.5–77.5
2097	7936.7–135.6	44.126.5–64.9
2098	82.737.9–166.4	49.823.6–84.5
2099	77.941–144.7	47.429.2–79.3
2100	80.840.2–141.3	47.924.4–79.7

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须知

一年中最高气温超过 35 °C 的天数，取全国平均。
来源：World Bank Climate Change Knowledge Portal, CMIP6 multi-model median。
虚线为CMIP6 模型中位数（SSP2-4.5，中间路径），是一种情景而非预报；阴影带为其模型第 10–90 百分位。
气候模型值为 CMIP6 各模型的中位数：2014 年及以前按历史排放模拟，此后按中间路径 SSP2-4.5 模拟；它们并非实测数据。

各图层如何运作、数据从何而来，以及它们无法告诉你什么：历年各国数据

巴西与危地马拉对比

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冲突

冲突死亡人数巴西：2022 年为 1,480 人死亡危地马拉：2022 年为 0 人死亡